Abstract
The temporal segmentation of a video sequence is one of the most important aspects for video processing, analysis, indexing, and retrieval. Most of existing techniques to address the problem of identifying the boundary between consecutive shots have focused on the uncompressed domain. However, decoding and analyzing of a video sequence are two extremely time-consuming tasks. Since video data are usually available in compressed form, it is desirable to directly process video material without decoding. In this paper, we present a novel approach for video cut detection that works in the compressed domain. The proposed method is based on both exploiting visual features extracted from the video stream and on using a simple and fast algorithm to detect the video transitions. Experiments on a real-world video dataset with several genres show that our approach presents high accuracy relative to the state-of-the-art solutions and in a computational time that makes it suitable for online usage.
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Almeida, J., Leite, N.J., Torres, R.S.: Comparison of video sequences with histograms of motion patterns. In: Int. Conf. Image Processing (ICIP 2011) (2011)
Almeida, J., Minetto, R., Almeida, T.A., Torres, R.S., Leite, N.J.: Robust estimation of camera motion using optical flow models. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Kuno, Y., Wang, J., Wang, J.-X., Wang, J., Pajarola, R., Lindstrom, P., Hinkenjann, A., Encarnação, M.L., Silva, C.T., Coming, D. (eds.) ISVC 2009. LNCS, vol. 5875, pp. 435–446. Springer, Heidelberg (2009)
Almeida, J., Minetto, R., Almeida, T.A., Torres, R.S., Leite, N.J.: Estimation of camera parameters in video sequences with a large amount of scene motion. In: Proc. of Int. Conf. Syst. Signals Image (IWSSIP 2010), pp. 348–351 (2010)
Almeida, J., Rocha, A., Torres, R.S., Goldenstein, S.: Making colors worth more than a thousand words. In: Int. Symp. Applied Comput. (ACM SAC 2008), pp. 1180–1186 (2008)
Bezerra, F.N., Leite, N.J.: Using string matching to detect video transitions. Pattern Anal. Appl. 10(1), 45–54 (2007)
Bouch, A., Kuchinsky, A., Bhatti, N.T.: Quality is in the eye of the beholder: meeting users’ requirements for internet quality of service. In: Int. Conf. Human Factors Comput. Syst. (CHI 2000), pp. 297–304 (2000)
Guimarães, S.J.F., Patrocínio Jr., Z.K.G., Paula, H.B., Silva, H.B.: A new dissimilarity measure for cut detection using bipartite graph matching. Int. J. Semantic Computing 3(2), 155–181 (2009)
Hanjalic, A.: Shot-boundary detection: Unraveled and resolved? IEEE Trans. Circuits Syst. Video Techn. 12(2), 90–105 (2002)
Koprinska, I., Carrato, S.: Temporal video segmentation: A survey. Signal Processing: Image Communication 16(5), 477–500 (2001)
Lee, S.W., Kim, Y.M., Choi, S.W.: Fast scene change detection using direct feature extraction from MPEG compressed videos. IEEE Trans. Multimedia 2(4), 240–254 (2000)
Lienhart, R.: Reliable transition detection in videos: A survey and practitioner’s guide. Int. J. Image Graphics 1(3), 469–486 (2001)
Pei, S.C., Chou, Y.Z.: Efficient MPEG compressed video analysis using macroblock type information. IEEE Trans. Multimedia 1(4), 321–333 (1999)
Pfeiffer, S., Lienhart, R., Kühne, G., Effelsberg, W.: The MoCA project - movie content analysis research at the University of Mannheim. In: GI Jahrestagung, pp. 329–338 (1998)
Whitehead, A., Bose, P., Laganière, R.: Feature based cut detection with automatic threshold selection. In: Enser, P.G.B., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A., Smeulders, A.W.M. (eds.) CIVR 2004. LNCS, vol. 3115, pp. 410–418. Springer, Heidelberg (2004)
Yeo, B.L., Liu, B.: Rapid scene analysis on compressed video. IEEE Trans. Circuits Syst. Video Techn. 5(6), 533–544 (1995)
Zhang, H., Kankanhalli, A., Smoliar, S.W.: Automatic partitioning of full-motion video. Multimedia Syst. 1(1), 10–28 (1993)
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Almeida, J., Leite, N.J., da S. Torres, R. (2011). Rapid Cut Detection on Compressed Video. In: San Martin, C., Kim, SW. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2011. Lecture Notes in Computer Science, vol 7042. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25085-9_8
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DOI: https://doi.org/10.1007/978-3-642-25085-9_8
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